CFHTLenS and RCSLenS cross-correlation with Planck lensing detected in fourier and configuration space

We measure the cross-correlation signature between the Planck cosmic microwave background (CMB) lensing map and the weak lensing observations from both the Red-sequence Cluster Lensing Survey and the Canada–France–Hawaii Telescope Lensing Survey. In addition to a Fourier analysis, we include the first configuration-space detection, based on the estimators 〈κCMBκgal〉 and 〈κCMBγt〉. Combining 747.2 deg2 from both surveys, we find a detection significance that exceeds 4.2σ in both Fourier- and configuration-space analyses. Scaling the predictions by a free parameter A, we obtain APlanckCFHT=0.68±0.31 and APlanckRCS=1.31±0.33⁠. In preparation for the next generation of measurements similar to these, we quantify the impact of different analysis choices on these results. First, since none of these estimators probes the exact same dynamical range, we improve our detection by combining them. Secondly, we carry out a detailed investigation on the effect of apodization, zero-padding and mask multiplication, validated on a suite of high-resolution simulations, and find that the latter produces the largest systematic bias in the cosmological interpretation. Finally, we show that residual contamination from intrinsic alignment and the effect of photometric redshift error are both largely degenerate with the characteristic signal from massive neutrinos, however the signature of baryon feedback might be easier to distinguish. The three lensing data sets are publicly available

Multiwavelength scaling relations in galaxy groups: a detailed comparison of GAMA and KiDS observations to BAHAMAS simulations

We study the scaling relations between the baryonic content and total mass of groups of galaxies, as these systems provide a unique way to examine the role of non-gravitational processes in structure formation. Using Planck and ROSAT data, we conduct detailed comparisons of the stacked thermal Sunyaev-Zel’dovich (tSZ) and X-ray scaling relations of galaxy groups found in the Galaxy And Mass Assembly (GAMA) survey and the BAHAMAS hydrodynamical simulation. We use weak gravitational lensing data from the Kilo Degree Survey to determine the average halo mass of the studied systems. We analyse the simulation in the same way, using realistic weak lensing, X-ray, and tSZ synthetic observations. Furthermore, to keep selection biases under control, we employ exactly the same galaxy selection and group identification procedures to the observations and simulation. Applying this comparison, we find that the simulations reproduce the richness, size, and stellar mass functions of GAMA groups, as well as the stacked weak lensing and tSZ signals in bins of group stellar mass. However, the simulations predict X-ray luminosities that are higher than observed for this optically selected group sample. As the same simulations were previously shown to match the luminosities of X-ray-selected groups, this suggests that X-ray-selected systems may form a biased subset. Finally, we demonstrate that our observational processing of the X-ray and tSZ signals is free of significant biases. We find that our optical group selection procedure has, however, some room for improvement

CFHTLenS and RCSLenS cross-correlation with Planck lensing detected in fourier and configuration space

We measure the cross-correlation signature between the Planck cosmic microwave background (CMB) lensing map and the weak lensing observations from both the Red-sequence Cluster Lensing Survey and the Canada–France–Hawaii Telescope Lensing Survey. In addition to a Fourier analysis, we include the first configuration-space detection, based on the estimators 〈κCMBκgal〉 and 〈κCMBγt〉. Combining 747.2 deg2 from both surveys, we find a detection significance that exceeds 4.2σ in both Fourier- and configuration-space analyses. Scaling the predictions by a free parameter A, we obtain APlanckCFHT=0.68±0.31 and APlanckRCS=1.31±0.33⁠. In preparation for the next generation of measurements similar to these, we quantify the impact of different analysis choices on these results. First, since none of these estimators probes the exact same dynamical range, we improve our detection by combining them. Secondly, we carry out a detailed investigation on the effect of apodization, zero-padding and mask multiplication, validated on a suite of high-resolution simulations, and find that the latter produces the largest systematic bias in the cosmological interpretation. Finally, we show that residual contamination from intrinsic alignment and the effect of photometric redshift error are both largely degenerate with the characteristic signal from massive neutrinos, however the signature of baryon feedback might be easier to distinguish. The three lensing data sets are publicly available

A new approach to cosmological perturbations in f(R) models

We propose an analytic procedure that allows to determine quantitatively the deviation in the behavior of cosmological perturbations between a given f(R) modified gravity model and a LCDM reference model. Our method allows to study structure formation in these models from the largest scales, of the order of the Hubble horizon, down to scales deeply inside the Hubble radius, without employing the so-called "quasi-static" approximation. Although we restrict our analysis here to linear perturbations, our technique is completely general and can be extended to any perturbative order.Comment: 21 pages, 2 figures; Revised version according to reviewer's suggestions; Typos corrected; Added Reference

LoCuSS: Testing hydrostatic equilibrium in galaxy clusters

We test the assumption of hydrostatic equilibrium in an X-ray luminosity selected sample of 50 galaxy clusters at $0.15<z<0.3$ from the Local Cluster Substructure Survey (LoCuSS). Our weak-lensing measurements of $M_{500}$ control systematic biases to sub-4 per cent, and our hydrostatic measurements of the same achieve excellent agreement between XMM-Newton and Chandra. The mean ratio of X-ray to lensing mass for these 50 clusters is $\beta_{\rm X}=0.95\pm0.05$, and for the 44 clusters also detected by Planck, the mean ratio of Planck mass estimate to LoCuSS lensing mass is $\beta_{\rm P}=0.95\pm0.04$. Based on a careful like-for-like analysis, we find that LoCuSS, the Canadian Cluster Comparison Project (CCCP), and Weighing the Giants (WtG) agree on $\beta_{\rm P}\simeq0.9-0.95$ at $0.15<z<0.3$. This small level of hydrostatic bias disagrees at $\sim5\sigma$ with the level required to reconcile Planck cosmology results from the cosmic microwave background and galaxy cluster counts

Cosmological distance indicators

We review three distance measurement techniques beyond the local universe: (1) gravitational lens time delays, (2) baryon acoustic oscillation (BAO), and (3) HI intensity mapping. We describe the principles and theory behind each method, the ingredients needed for measuring such distances, the current observational results, and future prospects. Time delays from strongly lensed quasars currently provide constraints on $H_0$ with < 4% uncertainty, and with 1% within reach from ongoing surveys and efforts. Recent exciting discoveries of strongly lensed supernovae hold great promise for time-delay cosmography. BAO features have been detected in redshift surveys up to z <~ 0.8 with galaxies and z ~ 2 with Ly-$\alpha$ forest, providing precise distance measurements and $H_0$ with < 2% uncertainty in flat $\Lambda$CDM. Future BAO surveys will probe the distance scale with percent-level precision. HI intensity mapping has great potential to map BAO distances at z ~ 0.8 and beyond with precisions of a few percent. The next years ahead will be exciting as various cosmological probes reach 1% uncertainty in determining $H_0$, to assess the current tension in $H_0$ measurements that could indicate new physics.Comment: Review article accepted for publication in Space Science Reviews (Springer), 45 pages, 10 figures. Chapter of a special collection resulting from the May 2016 ISSI-BJ workshop on Astronomical Distance Determination in the Space Ag

On the role of corticosterone in behavioral disorders, microbiota composition alteration and neuroimmune response in adult male mice subjected to maternal separation stress

Experiencing psychosocial adversities in early life such as maternal separation (MS) increases the risk of psychiatric disorders. Immune-inflammatory responses have imperative roles in the pathophysiology of psychiatric disorders. MS relatively changes the composition of intestinal microbiota leading to an overactivation of the hypothalamic-pituitary-adrenal (HPA) axis, and subsequently increases the corticosterone level. In this study, we aimed to evaluate the role of corticosterone in behavioral changes and microbiota modifications in a mouse model of MS afflicted neuroinflammatory response in the hippocampus. For this purpose, 180 min of MS stress was applied to mice at postnatal day (PND) 2-14 followed by behavioral tests including forced swimming test (FST), splash test, open field test (OFT) and elevated plus maze (EPM) at PND 50-52. For evaluating the role of corticosterone, mice were subjected to adrenalectomy. Using real-time RT-PCR, the expression of inflammatory genes was determined in the hippocampus and colon tissues. We found that MS provoked depressive- and anxiety-like behaviors in adult male mice. In addition, MS was able to active a neuroimmune response in the hippocampus, motivate inflammation and histopathologic changes in the colon tissue and modify the composition of gut microbiota as well. Interestingly, our findings showed that adrenalectomy (decline in the corticosterone level), could modulate the above-mentioned negative effects of MS. In conclusion, our results demonstrated that overactivation of HPA axis and the subsequent increased level of corticosterone could act, possibly, as the deleterious effects of MS on behavior, microbiota composition changes and activation of neuroimmune respons

RCSLenS: The Red Cluster Sequence Lensing Survey

We present the Red Cluster Sequence Lensing Survey (RCSLenS), an application of the methods developed for the Canada–France–Hawaii Telescope Lensing Survey (CFHTLenS) to the ∼785 deg2, multi-band imaging data of the Red-sequence Cluster Survey 2. This project represents the largest public, sub-arcsecond seeing, multi-band survey to date that is suited for weak gravitational lensing measurements. With a careful assessment of systematic errors in shape measurements and photometric redshifts, we extend the use of this data set to allow cross-correlation analyses between weak lensing observables and other data sets. We describe the imaging data, the data reduction, masking, multi-colour photometry, photometric redshifts, shape measurements, tests for systematic errors, and a blinding scheme to allow for more objective measurements. In total, we analyse 761 pointings with r-band coverage, which constitutes our lensing sample. Residual large-scale B-mode systematics prevent the use of this shear catalogue for cosmic shear science. The effective number density of lensing sources over an unmasked area of 571.7 deg2 and down to a magnitude limit of r ∼ 24.5 is 8.1 galaxies per arcmin2 (weighted: 5.5 arcmin−2) distributed over 14 patches on the sky. Photometric redshifts based on four-band griz data are available for 513 pointings covering an unmasked area of 383.5 deg2. We present weak lensing mass reconstructions of some example clusters as well as the full survey representing the largest areas that have been mapped in this way. All our data products are publicly available through Canadian Astronomy Data Centre at http://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/en/community/rcslens/query.html in a format very similar to the CFHTLenS data release

RCSLenS: The Red Cluster Sequence Lensing Survey

We present the Red Cluster Sequence Lensing Survey (RCSLenS), an application of the methods developed for the Canada–France–Hawaii Telescope Lensing Survey (CFHTLenS) to the ∼785 deg2, multi-band imaging data of the Red-sequence Cluster Survey 2. This project represents the largest public, sub-arcsecond seeing, multi-band survey to date that is suited for weak gravitational lensing measurements. With a careful assessment of systematic errors in shape measurements and photometric redshifts, we extend the use of this data set to allow cross-correlation analyses between weak lensing observables and other data sets. We describe the imaging data, the data reduction, masking, multi-colour photometry, photometric redshifts, shape measurements, tests for systematic errors, and a blinding scheme to allow for more objective measurements. In total, we analyse 761 pointings with r-band coverage, which constitutes our lensing sample. Residual large-scale B-mode systematics prevent the use of this shear catalogue for cosmic shear science. The effective number density of lensing sources over an unmasked area of 571.7 deg2 and down to a magnitude limit of r ∼ 24.5 is 8.1 galaxies per arcmin2 (weighted: 5.5 arcmin−2) distributed over 14 patches on the sky. Photometric redshifts based on four-band griz data are available for 513 pointings covering an unmasked area of 383.5 deg2. We present weak lensing mass reconstructions of some example clusters as well as the full survey representing the largest areas that have been mapped in this way. All our data products are publicly available through Canadian Astronomy Data Centre at http://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/en/community/rcslens/query.html in a format very similar to the CFHTLenS data release

Prediction and Topological Models in Neuroscience

In the last two decades, philosophy of neuroscience has predominantly focused on explanation. Indeed, it has been argued that mechanistic models are the standards of explanatory success in neuroscience over, among other things, topological models. However, explanatory power is only one virtue of a scientific model. Another is its predictive power. Unfortunately, the notion of prediction has received comparatively little attention in the philosophy of neuroscience, in part because predictions seem disconnected from interventions. In contrast, we argue that topological predictions can and do guide interventions in science, both inside and outside of neuroscience. Topological models allow researchers to predict many phenomena, including diseases, treatment outcomes, aging, and cognition, among others. Moreover, we argue that these predictions also offer strategies for useful interventions. Topology-based predictions play this role regardless of whether they do or can receive a mechanistic interpretation. We conclude by making a case for philosophers to focus on prediction in neuroscience in addition to explanation alone